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Débute 4 June 2026 11:04
Se termine 4 June 2026
Practical Machine Learning
Johns Hopkins University
35 Cours
L'Université Johns Hopkins est une université de recherche de renommée mondiale avec 9 écoles et campus à travers le monde. Elle propose plus de 260 programmes de diplômes, allant du premier cycle aux études supérieures et à la formation postdoctorale.
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Aperçu
Embark on a journey into the world of Artificial Intelligence and Machine Learning with Johns Hopkins University's practical course, offered through Coursera. This course demystifies the basic components involved in building and applying prediction functions, targeting both budding data scientists and data analysts.
Participants will gain foundational knowledge in essential concepts such as training and tests sets, the pitfalls of overfitting, and understanding error rates.
The curriculum extends to a variety of model-based and algorithmic machine learning methods, including but not limited to regression, classification trees, Naive Bayes, and random forests. Beyond theory, the course emphasizes practical application, guiding learners through the entire process of building prediction functions.
From data collection and feature creation to algorithms and evaluation, this course ensures a comprehensive understanding of the subject matter. Delve into the realms of Artificial Intelligence and Machine Learning with this rigorous yet accessible course, categorized under Artificial Intelligence Courses and Machine Learning Courses.
Enseigné par
Jeff Leek
